The present embodiments relate to processing medical diagnostic images.
For medical and clinical practice and research, imaging data may be collected and stored. One of the mechanisms to safeguard patients is to anonymize the imaging data. Anonymizing the data includes removing any identifying information about the individual patients in the data set, hence making the re-identification of those individuals very difficult. Anonymization of image data may be a compliance requirement for transfer of the data out of a hospital by software systems. In an example, medical data is anonymized inside the hospital network, and then transferred out to external systems, for example, a cloud network, to provide a more extensible information access point to the user, or to provide some software services that leverages cloud computing.
Anonymization of imaging data, however, causes issues for operators processing the imaging data. An operator may upload or transfer image data to an external system destination. The patient identifiable information, such as name, identifiers (IDs), or birthdates are removed. The removal of identifying information creates a cognitive challenge for the operator to remember to which patient the data that was uploaded belongs. Existing systems present the anonymized data back to the operator based on dates and ID numbers that may not be easily memorable. Mistakes due to the mental load and general fatigue of the operator may thus occur. For example, basic textual information such as IDs, dates or basic allowable information such as gender may require the operator to tediously read and sort out the information mentally.